Articles | Volume 23, issue 7
https://doi.org/10.5194/nhess-23-2625-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-2625-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jul 2023
Research article |
| 24 Jul 2023
| 24 Jul 2023
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
Davide Notti
Institute for Geo-Hydrological Protection (IRPI), Italian National
Research Council (CNR), Strada Delle Cacce 73, 10135 Turin, Italy
Martina Cignetti
Institute for Geo-Hydrological Protection (IRPI), Italian National
Research Council (CNR), Strada Delle Cacce 73, 10135 Turin, Italy
Institute for Geo-Hydrological Protection (IRPI), Italian National
Research Council (CNR), Strada Delle Cacce 73, 10135 Turin, Italy
Daniele Giordan
Institute for Geo-Hydrological Protection (IRPI), Italian National
Research Council (CNR), Strada Delle Cacce 73, 10135 Turin, Italy
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Total article views: 4,613 (including HTML, PDF, and XML)
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Cited
17 citations as recorded by crossref.
- Landslide vulnerability mapping using multi-criteria decision-making approaches: in Gacho Babba District, Gamo Highlands Southern Ethiopia L. Tadesse et al. 10.1007/s42452-024-05693-9
- Improve unsupervised Learning-based landslides detection by band ratio processing of RGB optical images: a case study on rainfall-induced landslide clusters L. Chen et al. 10.1080/19475705.2024.2363406
- Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
- The unsuPervised shAllow laNdslide rapiD mApping: PANDA method applied to severe rainfalls in northeastern appenine (Italy) D. Notti et al. 10.1016/j.jag.2024.103806
- A high-precision oasis dataset for China from remote sensing images J. Lin et al. 10.1038/s41597-024-03553-0
- Analysis of the Role of Precipitation and Land Use on the Size of the Source Area of Shallow Landslides A. Giarola et al. 10.3390/w15193340
- Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al. 10.3390/rs16101722
- Rapid Landslide Detection Following an Extreme Rainfall Event Using Remote Sensing Indices, Synthetic Aperture Radar Imagery, and Probabilistic Methods A. Chrysafi et al. 10.3390/land14010021
- ML-CASCADE: A machine learning and cloud computing-based tool for rapid and automated mapping of landslides using earth observation data N. Sharma & M. Saharia 10.1007/s10346-024-02360-3
- Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas D. Uwizeyimana et al. 10.1007/s11629-024-8869-4
- Continuous Satellite Image Generation from Standard Layer Maps Using Conditional Generative Adversarial Networks A. Šidlauskas et al. 10.3390/ijgi13120448
- A semi-supervised multi-temporal landslide and flash flood event detection methodology for unexplored regions using massive satellite image time series A. Deijns et al. 10.1016/j.isprsjprs.2024.07.010
- Assessing Many Image Processing Products Retrieved from Sentinel-2 Data to Monitor Shallow Landslides in Agricultural Environments R. Cavalli et al. 10.3390/rs16132286
- Detailed inventory and initial analysis of landslides triggered by extreme rainfall in the northern Huaiji County, Guangdong Province, China, from June 6 to 9, 2020 C. Xie et al. 10.1186/s40677-025-00311-1
- Flood susceptibility mapping to improve models of species distributions E. Ebrahimi et al. 10.1016/j.ecolind.2023.111250
- Automatic detection of landslide impact areas using Google Earth Engine Y. Yang et al. 10.1007/s44195-024-00078-2
- Spatiotemporal monitoring of droughts in Iran using remote-sensing indices S. Pouyan et al. 10.1007/s11069-023-05847-9
14 citations as recorded by crossref.
- Landslide vulnerability mapping using multi-criteria decision-making approaches: in Gacho Babba District, Gamo Highlands Southern Ethiopia L. Tadesse et al. 10.1007/s42452-024-05693-9
- Improve unsupervised Learning-based landslides detection by band ratio processing of RGB optical images: a case study on rainfall-induced landslide clusters L. Chen et al. 10.1080/19475705.2024.2363406
- Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
- The unsuPervised shAllow laNdslide rapiD mApping: PANDA method applied to severe rainfalls in northeastern appenine (Italy) D. Notti et al. 10.1016/j.jag.2024.103806
- A high-precision oasis dataset for China from remote sensing images J. Lin et al. 10.1038/s41597-024-03553-0
- Analysis of the Role of Precipitation and Land Use on the Size of the Source Area of Shallow Landslides A. Giarola et al. 10.3390/w15193340
- Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al. 10.3390/rs16101722
- Rapid Landslide Detection Following an Extreme Rainfall Event Using Remote Sensing Indices, Synthetic Aperture Radar Imagery, and Probabilistic Methods A. Chrysafi et al. 10.3390/land14010021
- ML-CASCADE: A machine learning and cloud computing-based tool for rapid and automated mapping of landslides using earth observation data N. Sharma & M. Saharia 10.1007/s10346-024-02360-3
- Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas D. Uwizeyimana et al. 10.1007/s11629-024-8869-4
- Continuous Satellite Image Generation from Standard Layer Maps Using Conditional Generative Adversarial Networks A. Šidlauskas et al. 10.3390/ijgi13120448
- A semi-supervised multi-temporal landslide and flash flood event detection methodology for unexplored regions using massive satellite image time series A. Deijns et al. 10.1016/j.isprsjprs.2024.07.010
- Assessing Many Image Processing Products Retrieved from Sentinel-2 Data to Monitor Shallow Landslides in Agricultural Environments R. Cavalli et al. 10.3390/rs16132286
- Detailed inventory and initial analysis of landslides triggered by extreme rainfall in the northern Huaiji County, Guangdong Province, China, from June 6 to 9, 2020 C. Xie et al. 10.1186/s40677-025-00311-1
3 citations as recorded by crossref.
- Flood susceptibility mapping to improve models of species distributions E. Ebrahimi et al. 10.1016/j.ecolind.2023.111250
- Automatic detection of landslide impact areas using Google Earth Engine Y. Yang et al. 10.1007/s44195-024-00078-2
- Spatiotemporal monitoring of droughts in Iran using remote-sensing indices S. Pouyan et al. 10.1007/s11069-023-05847-9
Latest update: 06 Mar 2025
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
We developed a cost-effective and user-friendly approach to map shallow landslides using free...
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